Coreferential Definite and Demonstrative Descriptions in French: A Corpus Study for Text Generation

Colloque avec actes et comité de lecture. internationale.International audienceThis paper presents a new classification for the use of definite and demonstrative descriptions, its application in a corpus analysis and the results of this analysis. The proposed classification is based on existing literature and extended to support the generation of definite and demonstrative NPs. The corpus analysis shows in particular, that subsequent mentions of a referent can perform two functions (repeating given information and/or introducing new information). The comparison between definite and demonstrative determiners leads to preliminary data for generation algorithms

Adaptación de una herramienta de Generación de Lenguaje Natural al idioma Español

En el presente Trabajo de Fin de Máster se ha realizado un análisis sobre las técnicas y herramientas de Generación de Lenguaje Natural (GLN), así como las modificaciones a la herramienta Simple NLG para generar expresiones en el idioma Español. Dicha extensión va a permitir ampliar el grupo de personas a las cuales se les transmite la información, ya que alrededor de 540 millones de personas hablan español. Keywords - Generación de Lenguaje Natural, técnicas de GLN, herramientas de GLN, Inteligencia Artificial, análisis, SimpleNLG.---ABSTRACT---In this Master's Thesis has been performed an analysis on techniques and tools for Natural Language Generation (NLG), also the Simple NLG tool has been modified in order to generate expressions in the Spanish language. This modification will allow transmitting the information to more people; around 540 million people speak Spanish. Keywords - Natural Language Generation, NLG tools, NLG techniques, Artificial Intelligence, analysis, SimpleNLG

A Meta-Algorithm for the Generation of Referring Expressions

This paper describes a new approach to the generation of referring expressions. We propose to formalize a scene as a labeled directed graph and describe content selection as a subgraph construction problem. Cost functions are used to guide the search process and to give preference to some solutions over others. The resulting graph algorithm can be seen as a meta-algorithm in the sense that defining cost functions in different ways allows us to mimic --- and even improve--- a number of wellknown algorithms.